Enhancing Climate Predictions with Integrated Attribution
Predicting climate patterns, especially over decades, is a challenging task, but it is crucial for preparing for the future. Each year, the World Meteorological Organization issues predictions of climate conditions for the next 1–5 years. However, what drives the predicted signals in these forecasts is poorly understood limiting our confidence in them. Mounting evidence suggests that these model simulations underestimate the magnitude of changes in atmospheric circulation, which can lead to extreme weather events like heatwaves, droughts, and floods. Hence, there is growing concern that existing climate models may not adequately capture these crucial atmospheric circulation shifts
Why Does it Matter?
Theme 2 aims to generate new insights into how our climate is changing on timescales ranging from years to decades. Accurate climate predictions are essential for governments, businesses, and communities to plan for the future. However, without a solid understanding of the underlying processes, predictions remain uncertain and potentially inaccurate, limiting their usefulness. By addressing these uncertainties and model shortcomings, Theme 2 seeks to make climate predictions more reliable, helping society better prepare for the impacts of climate change.
Developing Integrated Methods for Better Predictions
EXPECT is employing an integrated approach to climate prediction by combining three key components: attribution, prediction, and projection. Attribution involves identifying the specific factors driving climate changes, such as external forcing (e.g. greenhouse gases, aerosols, and solar radiation) and internal variations within climate systems. Prediction focuses on anticipating future changes, while projection looks further ahead to forecast long-term trends. We will work on correctly understanding, predicting, and projecting both elements: external forcing and internal variations.
A major focus of Theme 2 is understanding model errors and developing scientifically grounded calibration techniques to address these issues and use model differences to diagnose the real world situation. This process-based approach aims to enhance the precision and reliability of climate model forecasts. For instance, recent trends in Northern Hemisphere summer circulation, which have been linked to extreme weather events, are not well represented in current models. By better understanding these patterns and refining the models, EXPECT aims to produce more accurate and reliable predictions.
Leveraging New Knowledge for Reliable Climate Forecasts
Theme 2 emphasises calibrating the output provided by the models to correct known errors and reduce uncertainties. This calibration process involves using new insights into the physical drivers of climate change, gained through EXPECT’s research, to adjust the model predictions and projections. By doing so, EXPECT will help improve the consistency between current model predictions and real-world observations, leading to more accurate and confident climate predictions and projections.
In addition, Theme 2 will explore the potential of very high-resolution models and large ensemble simulations to further improve our understanding of climate variability and predictability. This approach will allow EXPECT to tackle complex questions about how different factors, such as ocean-atmosphere interactions, influence climate patterns over time.